Increased gut permeability and bacterial translocation are associated with fibromyalgia and myalgic encephalomyelitis/chronic fatigue syndrome: implications for disease-related biomarker discovery

Abstract

Background: There is growing evidence of the significance of gastrointestinal complaints in the impairment of the intestinal mucosal barrier function and inflammation in fibromyalgia (FM) and in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). However, data on intestinal permeability and gut barrier dysfunction in FM and ME/CFS are still limited with conflicting results. This study aimed to assess circulating biomarkers potentially related to intestinal barrier dysfunction and bacterial translocation and their association with self-reported symptoms in these conditions.

Methods: A pilot multicenter, cross-sectional cohort study with consecutive enrolment of 22 patients with FM, 30 with ME/CFS and 26 matched healthy controls. Plasma levels of anti-beta-lactoglobulin antibodies (IgG anti-β-LGB), zonulin-1 (ZO-1), lipopolysaccharides (LPS), soluble CD14 (sCD14) and interleukin-1-beta (IL-1β) were assayed using ELISA. Demographic and clinical characteristics of the participants were recorded using validated self-reported outcome measures. The diagnostic accuracy of each biomarker was assessed using the receiver operating characteristic (ROC) curve analysis.

Results: FM patients had significantly higher levels of anti-β-LGB, ZO-1, LPS, and sCD14 than healthy controls (all P < 0.0001). In ME/CFS patients, levels of anti-β-LGB, ZO-1, LPS, and sCD14 were significantly higher than controls, but lower than in FM (all P < 0.01), while there was no significant difference in IL-1β level. In the FM and ME/CFS cohorts, both anti-β-LGB and ZO-1 correlated significantly with LPS and sCD14 (P < 0.001 for both). In the FM group, both anti-β-LGB and ZO-1 were correlated significantly with physical and mental health components on the SF-36 scale (P < 0.05); whereas IL-1β negatively correlated with the COMPASS-31 score (P < 0.05). In the ME/CFS cohort, ZO-1 was positively correlated with the COMPASS-31 score (P < 0.05). The ROC curve analysis indicated a strong ability of anti-β-LGB, ZO-1, LPS and sCD14 to predictively distinguish between FM and ME/CFS from healthy controls (P < 0.0001).

Conclusion: Biomarkers of intestinal barrier function and inflammation were associated with autonomic dysfunction assessed by COMPASS-31 scores in FM and ME/CFS respectively. Anti-β-LGB antibodies, ZO-1, LPS, and sCD14 may be putative predictors of intestinal barrier dysfunction in these cohorts. Further studies are needed to assess whether these findings are causal and can therefore be applied in clinical practice.

Keywords: anti-beta-lactoglobulin; chronic fatigue syndrome; fibromyalgia; intestinal permeability; myalgic encephalomyelitis; zonulin.

Figure 1

Circulating biomarkers of intestinal permeability, bacterial translocation and inflammation in the study participants. Plasma levels of anti-β-LGB (A), ZO-1 (B), LPS (C), sCD14 (D), and IL-1β (E) in patients with FM (n = 22), ME/CFS (n = 30) and healthy controls (n = 26). Each dot denotes a single participant. Values are shown as mean ± SEM of duplicates and are representative of two independent experiments. The box extends from the 25^th to 75^th percentiles, the line represents the mean, and the whiskers indicate the range of minimum and maximum values. Significance at **P < 0.01, ***P < 0.001, and ****P < 0.0001 was calculated using the Kruskal-Wallis signed-rank test on normalized data. Anti-β-LGB, anti-beta-lactoglobulin antibodies; ZO-1, zonulin-1; LPS, lipopolysaccharides; sCD14, soluble CD14; IL-1β, interleukin-1 beta. n.s., not significant

Figure 2

Heatmap depicting color-coded Spearman’s correlation coefficients of circulating intestinal barrier function biomarkers and clinical outcome measures in the study participants. Correlation analysis of patients with FM (A), ME/CFS (B) and healthy controls (C) were evaluated using Spearman’s rank correlation test and FDR-adjusted P < 0.05. Pairwise Spearman’s rank correlation coefficients (rho) are depicted for each correlation and is presented by color intensity scale (at the top left of each panel). Heat color show standardized Z-scores (adjusted rho) across biomarkers and outcome measures. The color intensity is proportional to the strength of the association (rho value) ranging from red (positive correlations) to blue (negative correlations). Statistical significance was assessed using the Kruskal-Wallis test. FDR was calculated using Benjamini-Hochberg method. Statistical significance was set at *P < 0.05, **P < 0.01, and ***P < 0.001. Anti-β-LGB, anti-beta-lactoglobulin antibodies; ZO-1, zonulin-1; LPS, lipopolysaccharides; sCD14, soluble CD14; IL-1β, interleukin-1-beta.

Figure 3

ROC curve analysis of each intestinal barrier function biomarker to discriminate FM patients from healthy controls. IgG anti-β-LGB antibodies (A), ZO-1 (B), LPS (C), sCD14 (D), and IL-1β (E). ROC curves were used to explore the accuracy of each biomarker to discriminate between FM subjects and healthy controls. Cut-off values are shown for each biomarker with their respective sensitivity, specificity and optimal value. AUC values close to 1 indicate that a high true positive rate was achieved with false positive rate (ideal performance), while AUC values close to 0.5 indicate random performance. Anti-β-LGB, anti-beta-lactoglobulin antibodies; ZO-1, zonulin-1; LPS, lipopolysaccharides; sCD14, soluble CD14; IL-1β, interleukin-1-beta.

Figure 4

ROC curve analysis of each intestinal barrier function biomarker to discriminate ME/CFS patients from healthy controls. IgG anti-β-LGB antibodies (A), ZO-1 (B), LPS (C), sCD14 (D), and IL-1β (E) are displayed. ROC curves were used to analyze the accuracy of each biomarker to discriminate between ME/CFS subjects and healthy controls. Cut-off values are shown for each biomarker with their respective sensitivity, specificity and optimal value. AUC values close to 1 indicate that a high true positive rate was achieved with false positive rate (ideal performance), while AUC values close to 0.5 indicate random performance. Anti-β-LGB, anti-beta-lactoglobulin antibodies; ZO-1, zonulin-1; LPS, lipopolysaccharides; sCD14, soluble CD14; IL-1β, interleukin-1-beta.

Figure 5

ROC curve analysis of each intestinal barrier function biomarker to discriminate individuals with FM from ME/CFS. IgG anti-β-LGB antibodies (A), ZO-1 (B), LPS (C), sCD14 (D), and IL-1β (E) are displayed. ROC curves were used to analyze the accuracy of each biomarker to discriminate between ME/CFS subjects and healthy controls. Cut-off values are shown for each biomarker with their respective sensitivity, specificity and optimal value. AUC values close to 1 indicate that a high true positive rate was achieved with false positive rate (ideal performance), while AUC values close to 0.5 indicate random performance. Anti-β-LGB, anti-beta-lactoglobulin antibodies; ZO-1, zonulin-1; LPS, lipopolysaccharides; sCD14, soluble CD14; IL-1β, interleukin-1-beta.